Salt hydrate-based thermochemical energy storage (STCES) represents a promising pathway toward a sustainable energy future. The direct utilization of pure salt hydrates is severely hampered by inherent drawbacks, including deliquescence, particle agglomeration, poor cycle stability, and inferior heat-mass transfer capability, which lead to rapid capacity fading and poor system-level performance. This review provides a comprehensive assessment of the composite salt-in-porous-matrix (CSPM) strategy, which has proven to be one of the most widely investigated and promising routes to overcome these limitations through physical confinement and interfacial engineering. The structural characteristics and salt-loading compatibility of diverse porous hosts, including carbon-based materials, silica gels, metal-organic frameworks, natural minerals, and emerging polymer foams, are systematically evaluated in relation to their pore architecture, surface chemistry, and hydrothermal stability. Key preparation techniques, such as impregnation, in situ synthesis, foaming, and electrospinning, along with the targeted use of functional additives, are critically analyzed for their influence on energy storage density, hydration/dehydration kinetics, and long-term cyclability. The intrinsic trade-offs among these performance metrics, particularly the conflict between maximizing salt loading and maintaining structural integrity, are thoroughly discussed, emphasizing the necessity of multi-objective optimization. Furthermore, emerging data-driven approaches, including physics-informed neural networks and generative inverse design, are highlighted as transformative tools that can accelerate the discovery of optimal composite formulations and hierarchical pore topologies. Lastly, remaining challenges in scalable manufacturing, reactor-level integration, and techno-economic viability are identified, along with future research directions. This review offers fundamental insights and strategic guidance for the rational design and engineering of next-generation CSPMs for practical TCES applications.
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Li et al. (2026) studied this question.
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